We describe our experience implementing an intensive quality improvement cohort pilot focused on managing asymptomatic bacteriuria in 19 critical access hospitals. Participation in the pilot was high, and almost all sites identified an improvement goal and collected clinical data. Barriers to implementation included staffing shortages, turnover, and lack of bandwidth.

Background: In 2020, the American Society of Health System Pharmacist (ASHP) and Infectious Diseases Society of America (IDSA) published a consensus guideline for vancomycin management, recommending area under the curve (AUC) as the preferred monitoring strategy. These guidelines recommend doses of 15-20 mg/kg every 8 to 12 hours for most patients with normal renal function. However, in extreme body weights, standard dosing may deviate to provide a therapeutic AUC. The primary objective of this pharmacokinetic study is to evaluate the optimal vancomycin weight-based dosing strategy that achieves a therapeutic AUC of 400-600 stratified by body mass index (BMI). The secondary objective is to evaluate the incidence of acute kidney injury (AKI) based on BMI. Methods: Patients were identified from two sites within the Department of Veterans Affairs who received vancomycin for at least 48 hours and had at least one steady-state level from January 2015 through July 2022. Regimens with a frequency of ≤8 hours or patients with baseline creatine clearance of < 5 0 ml/min were excluded. Patients were categorized based on the Center for Disease Control BMI groups: healthy weight, overweight, or obese. The online vancomycin calculator, VancoPK©, was utilized to calculate AUC. Renal function at baseline and during vancomycin therapy was collected. Descriptive statistics were used for data analysis. Continuous outcomes were summarized using mean and standard deviation. The primary and secondary endpoints were analyzed using the analysis of variance and Fisher’s exact tests, respectively. Statistical significance was established at a p-value of < 0 .05. Results: A total of 347 unique vancomycin regimens were included: 120 in the healthy weight group, 101 in the overweight group, and 126 in the obese group. The average total daily doses that achieved a therapeutic AUC were 1971mg (15.6mg/kg/dose), 2298mg (15mg/kg/dose), and 2524mg (12.6mg/kg/dose) for the healthy weight, overweight, and obese groups, respectively. There was a statistically significant difference among these groups. AKI occurred in 10/254 (3.9%) unique patients: 2/89 (2.2%) in the healthy weight group, 3/71 (4.2%) in the overweight group, and 5/94 (5.3%) in the obese group. This did not reach statistical significance. Conclusions: Vancomycin dosing regimens largely followed guideline recommendations. However, the average vancomycin mg/kg/dose that achieved a therapeutic AUC decreased as BMI increased, which was a statistically significant trend. While further research is needed to draw clinically impactful conclusions, these findings suggest that a lower mg/kg vancomycin dose in obesity may be needed to achieve therapeutic targets.

Our systematic review and meta-analysis of 40 studies (n = 3,905,559) identified gastric acid suppressants, recent hospitalization, antibiotic exposure, and certain comorbidities as independent predictors of healthcare-associated Clostridioides difficile infection (HA-CDI) among adult inpatients. Targeted antibiotic stewardship and judicious use of gastric acid suppressants can reduce the incidence of HA-CDI.

This study characterized outpatient parenteral antimicrobial therapy (OPAT) orders and associated antimicrobial stewardship program (ASP) pharmacist recommendations made in a freestanding children’s hospital. Recommendations occurred in over 50% of orders, indicating an opportunity for the review of OPAT by ASP pharmacists.

Background: Group B Streptococcus (GBS) is one of the most common causes of bacterial sepsis in newborns. In 2002, the Center for Disease Control and Prevention (CDC) recommended universal screening of all pregnant women for GBS colonization and administering intrapartum prophylaxis to colonized pregnant women to prevent GBS infection in newborns. To identify racial disparities in GBS infections in Tennessee, we compared the incidence of early-onset GBS infection among Black and White infants from 2005-2021. Methods: GBS infections identified from normally sterile sites are reportable in Tennessee. We analyzed GBS data reported to surveillance systems from 2005 to 2021. We linked the surveillance data with the population data to calculate incidence rates. We excluded cases with unknown race status (9%) and other races (0.2%) as we do not have denominator data to calculate the incidence rate. Database linkage and data analyses were performed in SAS V.9.4. Results: A total of 399 early-onset GBS cases were reported from 2005–2021; 150 (37.59%) were Black, 212 (53.13%) were White, and 36 (9.02%) were of unknown race, and one (0.20%) reported as Other for race. While the incidence rates of early-onset GBS for all races declined from 0.23 per 1000 live births in 2005 to 0.18 per 1000 live births in 2021, Blacks experienced the largest decline in incidence from 0.6 per 1000 live births in 2005 to 0.37 in 2021. Among Whites, there was a slight decline in 2021 (0.13/1000 live births) compared to the rate in 2005 (0.21/1000 live births). The mean incidence rate of early onset GBS among Blacks (0.52 per 1000 live births) is significantly higher than the mean rates among Whites (0.20 per 1000 live births) (p value < 0 .001) from 2005 to 2021. Shelby County, one of the 95 counties in Tennessee, is predominantly Black (54.6%) and reported 27.8% of all early-onset GBS. Conclusion: There was a significant decline in early-onset GBS infections among Blacks and some reductions among Whites, indicating the effectiveness of the prevention strategies. However, Blacks have significantly higher rates than their White counterparts. In addition, 27.8% of the cases are reported from one county, signaling geographic disparities as well. Further investigation is warranted to identify risk factors and causes of observed racial and geographic disparities to help reduce the infection rate among vulnerable populations and high-risk geographic areas.

Background: The COVID-19 pandemic disrupted routine health services worldwide, including systems to detect antimicrobial resistance (AR). AR is a mounting global health threat with some studies showing the highest mortality rate from AR infection is in Sub-Saharan Africa (SSA). Antibiotic use is a major contributor to AR. We sought to characterize COVID-19-related changes to antibiotic use and AR detection capacity in two countries in SSA from 2019 to 2020. Methods: Health facilities (HF) in South Africa and Uganda were surveyed as part of a larger study assessing disruptions to essential health services in SSA in the context of COVID-19. Modified stratified random sampling of HF by facility level was conducted in regions with high COVID-19 cumulative prevalence. Hospital pharmacists were surveyed to identify perceived changes in antibiotic use. Among facilities with the capacity to detect AR, surveys were conducted with AR laboratory managers to identify perceived changes in staff, equipment, training, and supplies. Descriptive data analysis was conducted using frequencies and proportions. Results: A total of 39 HFs in South Africa and 45 HFs in Uganda responded to the antibiotic use survey. Increases in total antibiotic use from 2019 to 2020 were reported by 82% (23/28) of HF in South Africa and 68% (27/40) in Uganda. Increased use of antibiotics for multi-drug resistant bacteria (per World Health Organization Reserve classification) was reported by 36% (9/25) and 38% (8/21) of HFs in South Africa and Uganda, respectively. 19 HFs in South Africa and 12 HFs in Uganda responded to the AR detection capacity survey. HFs in both countries reported decreases in laboratory staff responsible for AR (33% [13/40] in South Africa and 31% [11/35] in Uganda). Decreased availability of reagents and consumables for bacteriology and antimicrobial susceptibility testing was reported by 50% (8/16) and 33% (4/12) of HFs, and decreased availability of specimen collection supplies for bacterial cultures was reported by 41% (7/17) and 42% (5/12) of HFs in South Africa and Uganda, respectively. Diversion of laboratory supplies was reported in both countries (32% [6/19] in South Africa and 25% [3/12] of HF in Uganda). Conclusions: HFs in South Africa and Uganda reported increases in antibiotic prescribing, a risk factor for increased AR, concurrently with disruptions in AR detection capacity during the early phases of the COVID-19 pandemic. These findings emphasize the importance of investing in bacteriology and AR testing in SSA and maintaining support during infectious disease pandemics.

Long-Term Care Facility (LTCF) residents are particularly vulnerable to infections due to factors such as advanced age, co-morbidities, and regular medication use. Data from American and European sources indicate an anticipated occurrence rate of 2 to 11 infections per 1000 patient-days (pds) in LTCFs. The incidence rate of Clostridioides difficile infections (CDI) is reported at 0.52 per 10,000 resident days. The research objectives aimed to assess infection epidemiology in Polish LTCFs. An observational prospective study was conducted on residents from five LTCFs (2 residential homes and 3 nursing homes) in southern Poland between September 2022 and September 2023, utilizing the definition from the pan-European HALT study. The study received approval from the Bioethics Committee of the JU (1072.6120.73.2022) and was funded by the Polish NCN grant No.2021/41/B/NZ6/00749. CDI was defined by positive toxins A and B enzyme immunoassays (EIA) and positive glutamate dehydrogenase (DHA) EIA. Results from the study, involving 250 residents, revealed 157 cases of Healthcare-Associated Infections (HAIs) excluding gastrointestinal and CDI, with an incidence rate of 1.97/1000 pds. Lower respiratory tract infections dominated with 77 cases, including 36 pneumonia cases (47%). Additionally, 25 cases of gastrointestinal infections were reported, including only 7 CDI cases, resulting in an incidence rate of 0.88 CDI per 10,000 pds. Norovirus was detected in only one case, while the microbiological results were negative in the remaining cases. The incidence rate among Polish LTCF residents was lower than expected, contrasting with the CDI incidence that aligned with other research findings. Notably, the etiology of diarrhea remained undetermined in 68% of cases.

Healthcare-associated viral respiratory infections (HA-VRIs) in a pediatric hospital decreased from 1.44 per 1000 patient days in 2019–0.43 and 0.38 in 2020–2021 during the SARS-CoV-2 pandemic but increased to 1.35 in 2022. The increase in HA-VRIs in 2022 coincided with the rise in community circulation of these organisms.

Introduction: Social determinants of health can impact healthcare-associated infections. Hospital-onset bacteremia (HOB) may lead to poor outcomes, increased length of stay, and increased cost of care. We explored the association of social determinants of health and HOB. Methods: We retrieved blood culture data at Stanford Health Care from May 2019 to October 2023. We identified blood cultures ordered ≥4 days of admission. To evaluate the association between social determinants of health and HOB, we employed an unsupervised machine learning approach (K-Means clustering) to discern patterns in HOB rates based on the Social Vulnerability Index (SVI). The SVI indicates the relative vulnerability of every U.S. Census tract. It ranks the tracts on 16 measures of vulnerability across 4 themes: socioeconomic factors, household characteristics, racial and ethnic minority status, and housing/transportation aspects. The number of clusters was determined using the Elbow Method (Figure 1). Results: Out of 209,947 blood cultures from 23,938 unique patients with a California address, we identified 81,653 blood cultures collected after 4 days (40%). The K-Means clustering algorithm identified 3 distinct clusters within the Californian census tracts, suggesting heterogeneity in the relationship between SVI and HOB (Figure 2). Cluster 1 had a higher SVI (median 0.73, range 0.46 – 0.99), with logistic regression indicating a positive SVI-HOB association (OR 4.84, 95% CI 4.02 – 4.81, p <.001). Cluster 2, had a median SVI of 0.29 (range 0.0009 – 0.78), also showed a positive association between SVI and HOB (OR 1.67, 95% CI 1.4 – 1.89, p <.001), aligning with trends of higher infection risks in more vulnerable groups. In contrast, Cluster 3 had a median SVI of 0.22 (range 0.002 –0.84). In this cluster, the SVI showed a negative association with HOB (OR 0.24, 95% CI 0.18 – 0.31, p <.001). Cluster 3 was the cluster with the least number of subjects (15,000, versus 21,761 for Cluster 1 and 29,762 for Cluster 2). Most subjects in Cluster 3 resided in Santa Clara County, whereas those in Clusters 1 and 2 were spread across Santa Clara, San Mateo, Alameda, Merced, and Sacramento Counties (Figure 3). Conclusions: Advanced techniques can be used to explore the complex interplay between social determinants of health and healthcare-associated infections and could guide the development of community-specific strategies to improve outcomes.

Background: Environmental contamination of surfaces is known to be one of the most common causes of healthcare associated infections (HAIs), with cleaning and disinfection of surfaces shown to reduce the incidence of HAIs and contribute to overall hospital cleanliness. Prior research showed that there was a relationship between a hospital’s performance on the Hospital Consumer Assessment of Healthcare Providers and Systems survey question on patient perception of cleanliness and their HAC score. However, this research was done prior to the COVID-19 pandemic. This study looked to examine if the pandemic changed the relationship between patient perception of cleanliness and HAC score performance. Method: A retrospective correlational study was performed to examine if the relationship between patient perception of cleanliness and the incidence of Clostridioides difficile (CDI) and Methicillin-Resistant Staphylococcus aureus (MRSA) HAIs, as defined by the facility’s HAC score, were affected by the COVID-19 pandemic. Multiple Center for Medicare and Medicaid Services (CMS) datasets were utilized for the study. There were approximately 2700 acute care facilities that reported data on the HCAHPS perception of cleanliness question and either a MRSA or CDI HAC score for the period of January 1, 2021, to December 31st, 2021. Basic descriptive statistics and Spearman’s rho correlation analyses were performed to examine the potential associations between the two scores. Result: For MRSA, the study found that as the percentage of patients who reported that their room was “always” clean increased, the hospital’s HAC score decreased (r= −0.141, p = < 0.001). Additionally, as the percentage of patients who reported their room was “never” clean increased, the hospital’s HAC score increased (r= 0.175, p = <0.001) For C. difficile, the analysis also revealed that as the percentage of patients who reported their room was “always” clean increased, there was not a significant change in the hospital’s HAC score (r= −0.023, p = 0.237). There was also not a significant change in the HAC score when the percentage of patients who reported their room as “never” clean increased (r= −0.012, p = 0.527).

Conclusion: The study found that for MRSA, a hospital’s performance on the HCAHPS performance on patient perception of cleanliness is related to their performance on their HAC score. This did not hold true when looking at C. difficile infections, which is in contrast to the prior evidence. Further research is needed to determine if there are specific factors that may have influenced this change.

Disclosure: Caitlin Crews-Stowe: Employee- ActivePure Medical

Among 143 cases of National Healthcare Safety Network (NHSN) catheter-associated urinary tract infections (CAUTI), 40% were considered catheter-associated asymptomatic bacteriuria (CA-ASB), and 18% clinical CAUTI. An alternative source of fever was present in 70% of CA-ASB. NHSN CAUTI may not be an effective metric for tracking hospital-level infection prevention efforts.

Background: Infection is one of the most common complications of cancer and cancer treatment. Most patients admitted for fever or infection come through the Emergency Department (ED), which is a primary site for blood culture collection. Contamination of blood cultures complicates the diagnoses, compromises quality of care, leads to unnecessary antibiotic exposure and increases financial burdens. It may also lead to unnecessary removal of central venous access devices or delay of critical therapy or procedures. At our institution, the contamination rate of blood cultures drawn in the ED was over twice that of the remainder of the hospital (2.8 versus 0.8), prompting this quality improvement project. Unlike on hospital floors, nurses, instead of phlebotomists, draw most blood cultures due to the urgency of managing suspected sepsis. Our aim was to decrease the ED contamination rate by 20 percent after the first PDSA cycle, and ultimately bring it on par with the remainder of the hospital. Methods: First, we compared ED contamination rates versus other hospital inpatient floors and outpatient centers over a three-month period. We then evaluated the contamination rates of ED nurses versus ED phlebotomists and peripheral versus central line blood draws. Process mapping and fishbone analysis helped identify practices contributing to higher contamination rates. Key drivers of these practices were diagrammed, and potential interventions were ranked on a prioritization matrix. Results: We identified use of alcohol rather than chlorhexidine swabs for peripheral disinfection and inconsistent techniques of blood draw by nurses as critical contributors to increased contamination rates in the ED. Our intervention was creating premade blood culture kits promoting the use of chlorhexidine swabs through availability and easy access in the fast-paced ED environment. Ten cubic centimeter (cc) syringes in the kits encouraged withdrawal of adequate blood samples in compliance with the 7-10 cc guideline. Designated nursing team leaders checked off ED nurses at the bedside, implementing education and adherence in using the blood culture collection kits. The average number of blood cultures in the emergency department was 1,400. A reduction in blood culture contamination from 2.46 percent to 1.89 percent was seen after two months. Conclusions: A guideline-driven, standardized blood culture collection process followed by ED nurses is vital to reducing blood culture contamination. Chlorhexidine is necessary to maintain the lowest contamination rates. Readily available premade blood culture kits improve compliance with materials and techniques associated with best practices.

Introduction: There are a number of tools available to healthcare epidemiologists for identification and investigation of healthcare-associated infections. For example, root cause analysis (RCA) is an evidence-based strategy for identifying process failures that resulted in infection. However, RCA is most valuable on a case-by-case basis. It is not an efficient tool for investigating numerous events that trend over time. Healthcare epidemiologists must use different strategies that are both efficient and powerful. A case-control study is a valuable option to investigate rare but recurrent infection events. The objective of this study was to demonstrate the utility of a case-control study design to detect attributable risk factors of cesarean section surgical site infections (SSI). Methods: We conducted a case-control study at a Level III childbirth center with data timeframe of January 1, 2021 to May 31, 2023. The project was approved by the institutions’ Quality Improvement Review Board prior to implementation. Cases were identified using the National Healthcare Safety Network (NHSN) SSI event criteria and included all levels of SSI. Controls were selected from the NHSN surgical denominator and were matched randomly without replacement by age at a 1:4 ratio. Variables were identified in collaboration with stakeholders based on known risk factors for SSI and abstracted manually. Analyses were conducted in Stata/MP version 17.0, and we performed multivariable conditional logistic regression with an alpha of 0.05 as threshold for statistical significance. The model was built according to a priori hypotheses and results from bivariate analysis of individual risk factors. Results: There were 32 SSI among 1709 cesarean deliveries, and all cases successfully matched with 4 controls for an analytic sample of 128. Bivariate analyses identified 7 relevant variables for inclusion in the multivariable model which narrowed down significant risk factors to 3: operative time (in minutes), post-operative chlorhexidine gluconate (CHG) bathing, and number of people in the operating room. Assessment of fit indices suggested an excellent fit with pseudo R-square of 0.526. Conclusions: This study demonstrated the utility of a case-control study design to identify attributable risk factors for relatively rare but significantly trending infection events. Not only is the design more efficient (e.g., time needed to abstract 50 data points for each patient), but it also employs statistical analyses that are often lacking in case-by-case investigations or RCA. It also has the power to narrow down risk factors for focused prevention efforts to get “the most bang for the buck.”

Background: At a comprehensive cancer center, hundreds of patients are screened daily for infections requiring the implementation of isolation precautions. Discontinuation of precautions is determined by negative testing, resolution of infection, or other criteria. Determining appropriate discontinuation of isolation precautions is labor intensive for Infection Preventionists (IPs). An unintended consequence of manual discontinuation is that numerous patients remain on isolation indefinitely. This was amplified during the COVID-19 pandemic when thousands of patients were placed on isolation precautions. Using electronic health record (EHR) tools, opportunities for process improvements were developed. Our goal was to establish an automated method to resolve isolation precautions. We aimed to decrease the number of manually resolved precautions by 25% each fiscal year (FY), compared to our baseline of activity in FY 2019 (FY19). Our secondary aim was to automate adding and resolving precautions when testing is initiated for suspected transmissible conditions (rule-out testing features).

Methods: Infection Control (IC) collaborated with EHR analysts to build tools to automate a process for appropriate isolation discontinuation. We reviewed our internal data in conjunction with evidence-based guidelines and started with acute, short-term infections that do not require repeat testing or cultures. Expiration dates were established for these infections to resolve automatically after meeting criteria. A secondary review determined that additional infections could be added safely to this process. The secondary aim of establishing rule-out testing was implemented for respiratory viral panels (including SARS-COV-2) and C. difficile testing. When testing was ordered for these conditions, a suspect-infection status and alert for precautions were automatically added to patients’ EHR banners. If the assay resulted negative, the suspect-infection status was automatically removed from their chart. Results: Our baseline of active infections in FY19 was approximately 2,700 cases. From FY19 through FY23, 123,115 infections were added to our patients, and 128,422 infections were resolved. In the first year of implementation, there was a 58% decrease in the number of manually resolved cases. From the initiation of our project through the end of FY23, manual discontinuation of precautions has decreased by 88%. Conclusions: We successfully implemented a process improvement project to appropriately remove patients from isolation precautions automatically using EHR tools, which resulted in reduced labor on our IPs and patient time spent on isolation restrictions. Additional benefits from this process improvement extend to decreasing unnecessary costs to the patient and the organization, better stewardship of supply/resources, and improving patient satisfaction.

Long-term care pharmacy dispensing data from 2013 to 2021 were used to characterize antibiotic prescribing data in U.S. long-term care facilities. Overall antibiotic prescribing rates decreased from 2013 to 2021, mostly due to decreases in fluoroquinolones and macrolides. Tracking antibiotic use in long-term care settings can help identify opportunities for optimizing prescribing practices.

Background: Infection Prevention (IP) practices in ambulatory care are often reactive and many communicable diseases in the community often do not fall onto IP’s radar until the patient becomes ill enough to seek inpatient services. The gap between ambulatory and inpatient care can lead to increased transmission and illness severity. Early identification has substantial impacts on timely implementation of IP mitigation strategies, appropriate handoff upon entry into other care settings, and timely reporting to public health organizations. Current IP processes underutilize electronic health record (EHR) capabilities by relying upon lab driven notifications. This project sought to redesign the IP’s workflows, advancing the health system beyond the acute care setting and into the ambulatory care setting by adding the power of diagnosis codes to close a practice gap. Method: Infection Prevention and Information Technology collaborated to build silent best practice advisories (BPAs) in the EHR that utilized diagnosis codes related to Varicella zoster (VZV) infection charted by ambulatory care providers. These BPAs function by triggering infection statuses that populate the patient chart and include instructions to front line staff on personal protective equipment (PPE) requirements. These BPAs also trigger real-time notifications to the IP team to determine the validity of the infection status and exposure work-up necessity. Chart reviews of diagnosis codes utilized in pre and post intervention timeframes were completed to understand the impact of the silent BPAs. Percentages of patients captured, and Healthcare Worker (HCW) exposure reviews reported were evaluated to demonstrate effectiveness. Plan, Do, Study, Act (PDSA) was utilized to respond to gaps, increase efficiency, and limit erroneous infection statuses. Result: The one-year pre-intervention period revealed 36 total diagnosis codes used for Varicella zoster (VZV) infection; 3% of these infection cases were captured and 4% of eligible cases were reported for HCW exposure review. The one-year post intervention period revealed 40 total diagnosis codes used for VZV infection; 80% of these infection cases were captured and 70% of eligible cases were reported for HCW exposure review. PDSA quality improvement cycles allowed for refinement of the BPA logic that further increased infection cases captured to 100% with 100% of eligible cases reported for HCW exposure review. Conclusion: Utilizing the EHR, the organization appreciated enhanced identification of patients in real-time with VZV infection that allowed for appropriate mitigation strategies to be implemented. This proactive workflow design helps minimize the risk of transmission between ambulatory and acute settings and facilitated HCW exposure reviews.